Abstract
Optical frequency domain imaging (OFDI) can identify key components related to plaque vulnerability but can suffer from artifacts that could prevent accurate identification of lipid rich regions. In this paper, we present a model of depth resolved spectral analysis of OFDI data for improved detection of lipid. A quadratic Discriminant analysis model was developed based on phantom compositions known chemical mixtures and applied to a tissue phantom of a lipid-rich plaque. We demonstrate that a combined spectral and attenuation model can be used to predict the presence of lipid in OFDI images.